CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction
Lixin Yang, Xinyu Zhan, Kailin Li, Wenqiang Xu, Jiefeng Li, Cewu Lu
We highlight contact in the hand-object interaction modeling task by proposing an
explicit representation named Contact Potential Field (CPF). In CPF, we treate each contacting
vertex pair as a spring-mass system, Hence the whole system forms a potential filed with minimal
at the grasp position.
HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and
Jiefeng Li, Chao Xu, Zhicun Chen, Siyuan Bian, Lixin Yang, Cewu Lu
We bridge the gap between body mesh estimation and 3D keypoint estimation.
We propose a novel hybrid inverse kinematics solution (HybrIK).
HybrIK directly transforms accurate 3D joints to relative body-part rotations for 3D body mesh
via the twist-and-swing decomposition.
HandTailor: Towards High-Precision Monocular 3D Hand Recovery
Jun Lv, Wenqiang Xu, Lixin Yang, Sucheng Qian, Chongzhao Mao, Cewu Lu
We introduce a novel framework HandTailor, which combines a learning-based hand module and an
optimization-based tailor module to achieve high-precision
hand mesh recovery from a monocular RGB image. The proposed hand module unifies perspective
weak perspective projection in a single network
towards accuracy-oriented and in-the-wild scenarios.
BiHand: Recovering Hand Mesh with Multi-stage Bisected Hourglass Networks
Lixin Yang, Jiasen Li, Wenqiang Xu, Yiqun Diao, Cewu Lu
We introduce an end-to-end learnable model, BiHand, to recover hand mesh from RGB image.
BiHand adopts a novel bisecting design which allows the networks to encapsulate two closely related
information (e.g. 2D keypoints and silhouette) to facilitate network performance.
This guy has an awesome website